Probabilistic Programming: A Modern Bayesian Workflow || Peadar Coyle
Probabilistic Programming is a new paradigm enabling a better understanding of uncertainty. I introduce a modern Bayesian workflow and explanation of Hamiltonian Monte Carlo - how it fails and how you debug it.
EVENT:
PyData London Meetup #48
SPEAKER:
Peadar Coyle
PERMISSIONS:
PyData Organizer provided Coding Tech with the permission to republish this video.
CREDITS:
Original video source: https://www.youtube.com/watch?v=0kRytJZcHVw
Видео Probabilistic Programming: A Modern Bayesian Workflow || Peadar Coyle канала Coding Tech
EVENT:
PyData London Meetup #48
SPEAKER:
Peadar Coyle
PERMISSIONS:
PyData Organizer provided Coding Tech with the permission to republish this video.
CREDITS:
Original video source: https://www.youtube.com/watch?v=0kRytJZcHVw
Видео Probabilistic Programming: A Modern Bayesian Workflow || Peadar Coyle канала Coding Tech
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Probabilistic Programming in the Real World - Zach AnglinAndrew Rowan - Bayesian Deep Learning with Edward (and a trick using Dropout)A Random Walk & Monte Carlo Simulation || Python Tutorial || Learn Python ProgrammingTutorial: Probabilistic programming - a categorical tutorial (Sam Staton)Get started with using TensorFlow to solve for regression problems (Coding TensorFlow)Dave Blei: "Black Box Variational Inference"Julia: Is it better than Python? [Everything you need to know in 2020]Vincent Warmerdam: Winning with Simple, even Linear, Models | PyData London 2018Why Isn't Functional Programming the Norm? – Richard FeldmanThe State of the Art for Probabilistic Programming - Thomas Wiecki | PyData Global 2021TensorFlow 2.0 Tutorial For Beginners | TensorFlow Demo | Deep Learning & TensorFlow | SimplilearnUber Practitioner SessionJakob Hoydis - Recent Progress in End-to-End Learning for the Physical LayerSolving Optimization Problems with MATLAB | Master Class with Loren ShureA Case for Oxidation: The Rust Programming Languagepomegranate | Fast and Flexible Probabilistic Modeling in Python | SciPy 2017 | Jacob Schreiber10 Julia Packages You Should Learn for Data Science (in 2020)Sean Matthews, Jannes Quer: Time series modelling with probabilistic... | PyData Berlin 2019Probabilistic programming and meta-programming in Clojure - Vikash Mansinghka